Virtual Sensor Process Model for Machine Retrofitting
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Solution Overview
Problem
Existing virtual sensor systems fail to effectively address inter-correlations between measured parameters, leading to inefficiencies and increased costs due to reliance on physical sensors, which can be costly and unreliable, and pose challenges in determining sensor types and qualities for modern machines, especially during retrofitting.
Innovation Solution
A method and system for creating virtual sensors by establishing process models that interrelate sensing and measured parameters, allowing for the calculation of sensing parameters and their provision to control systems, and enabling the creation of virtual sensors based on correlated physical sensors to replace or supplement physical sensors, thereby reducing costs and improving reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical sensors are used to directly measure physical phenomena, then measurement accuracy is improved, but product cost increases and reliability decreases due to sensor failure risks
Solution Approach 1:
The patent creates virtual sensors that copy the measurement function of physical sensors by computing sensing parameters from measured parameters through process models. Instead of relying on physical sensor hardware, the system uses computational models that replicate sensor behavior, thereby eliminating physical sensor failures while maintaining measurement accuracy.
Solution Approach 2:
The patent replaces the mechanical/physical sensor system with a computational/software-based virtual sensor system. The process models and parameter calculations substitute for physical sensing hardware, transforming a hardware-dependent measurement system into a software-based solution that improves reliability while maintaining measurement precision.
2Measurement precision
If high quality physical sensors are used for all sensor functions, then measurement precision is improved, but product cost increases significantly
Solution Approach 1:
The patent applies local quality by using high precision virtual sensors only where needed based on the specific requirements of each sensing parameter. The system evaluates which parameters require virtual sensing and applies computational models selectively, rather than uniformly across all sensor functions, thereby optimizing cost while maintaining necessary precision.
Solution Approach 2:
The patent changes the fundamental parameter of sensor implementation from physical hardware to computational software. By transforming sensor functionality from a hardware parameter to a software calculation parameter, the system eliminates the need for expensive high-quality physical sensors while maintaining measurement precision through process models.
3Adaptability or versatility
If new physical sensors are installed for retrofitting machines with new functionalities, then functionality is improved, but device complexity and cost increase due to hardware installation requirements
Solution Approach 1:
The patent copies the sensing capability needed for new functionalities through virtual sensors rather than installing new physical sensors. The process models replicate the measurement function required for new machine functionalities, enabling retrofitting without adding physical hardware complexity.
Solution Approach 2:
The patent creates a universal virtual sensor platform that can provide multiple sensing functions through software models. A single virtual sensor system can serve multiple sensing needs by loading different process models, thereby enabling retrofitting with new functionalities without requiring separate physical sensors for each function.
4Ease of manufacture
If conventional virtual sensor techniques are used, then sensor cost is reduced, but measurement accuracy deteriorates due to failure to address inter-correlations between parameters
Solution Approach 1:
The patent merges multiple measured parameters into a unified process model that captures their inter-correlations. Instead of treating parameters independently, the system combines them in integrated computational models that reflect the actual relationships between parameters, thereby improving sensing parameter accuracy while maintaining cost effectiveness.
Solution Approach 2:
The patent implements feedback mechanisms where the virtual sensor system continuously refines its parameter calculations based on the inter-correlations observed in the process data. The system uses the relationships between measured parameters to feedback and improve the accuracy of computed sensing parameters, overcoming the limitations of conventional independent parameter approaches.
Data Source
AI summary
A method is provide for providing sensors for a machine. The method may include obtaining data records including data from a plurality of sensors for the machine and determining a virtual sensor corresponding to one of the plurality of sensors. The method may also include establishing a virtual sensor process model of the virtual sensor indicative of interrelationships between at least one sensing parameters and a plurality of measured parameters based on the data records and obtaining a set of values corresponding to the plurality of measured parameters. Further, the method may include calculating the values of the at least one sensing parameters substantially simultaneously based upon the set of values corresponding to the plurality of measured parameters and the virtual sensor process model and providing the values of the at least one sensing parameters to a control system.